The goal of this project is to develop a novel cyber-physical system (CPS) for performing multimodal image-guided robot-assisted minimally invasive surgeries (MIS). The approach is based on: (1) novel quantitative analysis of multi-contrast data, (2) control that uses this information to maneuver conformable robotic manipulators, while adjusting on-the-fly scanning parameters to acquire additional information, and (3) human-information/machine-interfacing for comprehensive appreciation of the physical environment. The intellectual merit arises from the development of: (1) a CPS that relies on "real" and "real-time" data, minimizing parametric and abstracted assumptions, extracts and matures information from a dynamic physical system (patient and robot) by combining management of data collection (at the physical sensor site) and data analysis (at the cyber site), (2) "smart sensing", to control data acquisition based on disruptive or situation altering events, (3) control coordination by interlacing sensing, control and perception, and the incorporation of steerable tools. The societal impact arises from contributions to a leap in MIS: from "keyhole" visualization (i.e., laparoscopy) to in-situ real-time image guidance, thereby enabling a wider range of MIS. This will directly benefit patients and their families (faster recovery/reduced trauma). Economic impact arises from the cost-effectiveness of MIS to the health care system, faster patient return to the workplace, and technology commercialization. The project will integrate research and education, diversity and outreach, by enhancing current and introducing new research-intensive courses in Cyber-physical Systems, Medical Imaging and Medical Robotics, and dissemination via trans-institutional collaborations, a comprehensive web site, multimedia web-seminars, and distribution to high schools.

The objective of this research is to develop an intuitive user interface for functional electrical stimulation (FES), which uses surgically-implanted electrodes to stimulate muscles in spinal cord-injured (SCI) patients. The challenge is to enable high-level tetraplegic patients to regain the use of their own arm. The approach is to develop a multi-modal Bayesian user-intent decoder; use natural muscle synergies to generate appropriate low-dimensional muscle activation signals in a feedforward controller; develop a feedback controller to enhance the performance of the feedforward controller; and test the system with SCI patients on daily living tasks, such as reaching, grasping, and eating. The challenge problem of restoring arm use to SCI patients will lead to new design principles for cyber-physical systems interfacing neural and biological systems with engineered computation and electrical power systems. The tight integration of the proposed user interface and controller with the users own control system requires a deep understanding of biological design principles such as nested feedback loops at different time and length scales, noisy signals, parallel processing, and highly coupled neuromechanical systems. This work will lead to new technology that dramatically improves the lives of spinal cord-injured patients. These patients often have no cognitive impairment and have long life spans after injury. The goal is to enable these patients to eat, reach, and grasp nearby objects. These tasks are critical for independent living and quality of life. This work will also help train a new generation of students in human-machine interfaces at the undergraduate, graduate, and postdoctoral levels.

CPS: Small: Collaborative Research: Localization and System Services for SpatioTemporal Actions in Cyber-Physical Systems The objective of this research is to develop models, methods and tools for capturing and processing of events and actions in cyber-physical systems (CPS) in a manner that does not violate the underlying physics or computational logic. The project approach uses a novel notion of cyber-physical objects (CPO) to capture the mobility and localization of computation in cyber-physical systems using recent advances in geolocation and the Internet infrastructure and supports novel methods for spatiotemporal resource discovery. Project innovations include a model for computing spatiotemporal relationships among events of interests in the physical and logical parts of a CPS, and its use in a novel cyberspatial reference model. Using this model the project builds a framework for locating cyber-physical application services and an operating environment for these services. The project plan includes an experimental platform to demonstrate capabilities for building new OS services for CPS applications including collaborative control applications drawn from the intermodal transportation system. The project will enable design and analysis of societal scale applications such as the transportation and electrical power grid that also include a governance structure. It will directly contribute to educating an engineering talent pool by offering curricular training that range from degree programs in embedded systems to seminars and technology transfer opportunities coordinated through the CalIT2 institute at UCSD and the Institute for Sensing Systems (ISS) at OSU. The team will collaborate with the non-profit Milwaukee Institute to explore policies and mechanisms for enterprise governance systems.

Objectives and approaches. The objective of this research is to create a novel Cyber-Physical System, a self-reconfiguring ?second skin orthotic sleeve? consisting of programmable materials. The orthotic sleeve, worn over one or more limbs of brain-injured individuals, may restore brain function by promoting enriched exploration of self-produced limb movements. The approach consists of three steps (1) micro-fabricating sheets with embedded sensors and muscle-like collections of force-producing actuators, (2) conducting longitudinal recordings of kicking by typically developing and preterm brain-injured infants who wear a sensing, but not actuated micro-fabricated second skin, and (3) developing biologically-inspired programming techniques to help determine an algorithm with which the second skin embedded actuators may adaptively assist the ever-changing developmental pattern of infant kicking. The technology can be applied to many mobility-impaired populations,including children and adults with brain injury, the ageing population, and injured soldiers. The project will inform basic scientific and engineering research in areas such as formation of architectural structures by large-scale multi-agent robotic systems, and self-organization of swarming small-scale agents that act autonomously in cooperation with biological systems. The multi-institutional effort of this research endeavor will positively impact undergraduate and graduate science education via explorations of the intersection of biology and computation in cyber-physical systems. Innovation, teamwork, and the value of communication are encouraged. These efforts will promote education of an American work force that is technically expert, scientifically comprehensive, and socially aware to sustain national excellence in a future increasingly based on technologically complex systems.

The objective of this research is to discover new fundamental principles, design methods, and technologies for realizing distributed networks of sub-cm3, ant-sized mobile micro-robots that self-organize into cooperative configurations. The approach is intrinsically interdisciplinary and organized along four main thrusts: (1) Algorithms for distributed coordination and control under severe power, communication, and mobility constraints. (2) Electronics for robot control using event-based communication and computation, ultra-low-power radio, and adaptive analog-digital integrated circuits. (3) Locomotion devices and efficient actuators using rapid-prototyping and MEMS technologies that can operate robustly under real-world conditions. (4) Integration of the algorithms, electronics, and actuators into a fleet of ant-size micro-robots. No robots at the sub-cm3 scale exist because their development faces a number of open challenges. This research will identify and determine means for solving these challenges. In addition, it will provide new solutions to outstanding questions about resource-constrained algorithms, architectures, and actuators that can be widely leveraged in other applications. The PIs will adopt a co-design philosophy that promotes cross-disciplinary research and tight collaboration. Networks of ant-sized robots are expected to be useful in disaster relief, manufacturing, warehouse management, and ecological monitoring, as well as in new unforeseen applications. In addition, the new methods and principles proposed here can be transitioned to other highly-distributed and resource-constrained engineering problems, such as air-traffic control systems. This research program will train Ph.D. students with unique skills in the design of hybrid distributed networks and it will involve undergraduate students, particularly underrepresented minorities and women.

The objective of this research is to develop principles and tools for the design of control systems using highly distributed, but slow, computational elements. The approach of this research is to build an architecture that uses highly parallelized, simple computational elements incorporating nonlinearities, time delay and asynchronous computation as integral design elements. Tools for the design of non-deterministic protocols will be developed and demonstrated using an existing multi-vehicle testbed at Caltech. The motivation for using "slow computing" is to develop new feedback control architectures for applications where computational power is extremely limited. Examples of such systems are those where the energy usage of the system must remain small, either due to the source of power available (e.g. batteries or solar cells) or the physical size of the device (e.g. microscale and nanoscale robots). A longer term application area is in the design of control systems using novel computing substrates, such as biological circuits. A critical element in both cases is the tight coupling between the dynamics of the underlying process and the temporal properties of the algorithm that is controlling it. The implementation plan for this project involves students from multiple disciplines (including bioengineering, computer science, electrical engineering and mechanical engineering) as well as at multiple experience levels (sophomores through PhD students) working together on a set of interlinked research problems. The project is centered in the Control and Dynamical Systems department at Caltech, which has a strong record of recruiting women and underrepresented minority students into its programs.

The objective of this research is to develop an integrated methodology for control system design in situations where disturbances primarily result from routine human behavior, as, for example, in future artificial pancreas systems where meals and exercise are the main disturbances affecting blood glucose concentration. The approach is to recognize that human behavioral disturbances (i) are generally random but cannot be treated as zero-mean white noise processes and (ii) occur with statistical regularity but cannot be treated as periodic due to natural variation in human behavior. This emerging class of problems requires (i) the derivation of new mathematical representations of disturbances for specific applications and (ii) the formulation of new stochastic control models and algorithms that exploit statistical regularity in the disturbance process. The intellectual merit of the proposed research stems from the fact that it explicitly recognizes a new class of disturbances, human behavioral disturbances, seeking to develop an integrated approach to statistically characterizing and responding to future perturbations, adapting gracefully to uncertainty about the future. The anticipated research outcomes will be relevant in diverse fields, including stochastic hybrid control and human automation interaction. As a broader implication, the proposed research will enable the design of future field deployable artificial pancreas systems, potentially improving the lives of 1.5 million Americans suffering from Type 1 diabetes. With help from the two graduate students funded by the project, the principle investigator will supervise a Capstone design course, exposing undergraduates to various aspects of control under human behavioral disturbances.

The objective of this research is to develop new scientific and engineering principles, algorithms and models for the design of battery powered cyber-physical systems whose computational substrates include high-performance multiprocessor systems-on-chip. The approach is to design control tasks that guarantee performance and meet criteria for battery operation time. Task schedulers are co-designed to balance the computing load across the multiple processors, and to control the physical plant together with the control tasks. The controller and scheduler will be integrated with battery management algorithms through a systems theory approach so that the methods are provably correct with justfiable performance. Intellectual Merit: The program will create progress in digital and hybrid control theory that keeps up with the recent trend of using multiprocessor systems-on-chips for control and robotic applications. The mechanism for the migration of control tasks between multiple processors will respect physical and thermal performance. A novel battery dynamic discharge model is developed, which may be applied to context when the discharge current of batteries cannot be predicted by existing static battery models. Broader Impacts: Collaborations with industrial partners have been set up. The program offers multidisciplinary training in cyber-physical systems. A teaching and outreach lab is in place to host K-12 student teams that participate in robot competitions, and has become an Explorer Post for Boy Scout of America.

The objective of this research is to develop technologies to improve the efficiency and safety of the road transportation infrastructure. The approach is to develop location-based vehicular services combining on-board automotive computers, in-car devices, mobile phones, and roadside monitoring/surveillance systems. The resulting vehicular Cyber Physical Systems (CPS) can reduce travel times with smart routing, save fuel and reduce carbon emissions by determining greener routes and commute times, improve safety by detecting road hazards, change driving behavior using smart tolling, and enable measurement-based insurance plans that incentivize good driving. This research develops distributed algorithms for predictive travel delay modeling, feedback-based routing, and road hazard assessment. It develops privacy-preserving protocols for capturing and analyzing data and using it for tasks such as congestion-aware tolling. It also develops a secure macro-tasking software run-time substrate to ensure that algorithms can be programmed centrally without explicitly programming each node separately, while ensuring that it is safe to run third-party code. The research focuses on re-usable methods that can benefit multiple vehicular services, and investigates which lessons learned from this vehicular CPS effort generalize to other situations. Road transportation is a grand challenge problem for modern society, which this research can help overcome. Automobile vendors, component developers, and municipal authorities have all shown interest in deployment. The education plan includes outreach to local K-12 students and a new undergraduate course on transportation from a CPS perspective, which will involve term projects using the data collected in the project

The objective of this research is to enable operation of synthetic and cyborg insects in complicated environments, such as outdoors or in a collapsed building. As the mobile platforms and environment have significant uncertainty, learning and adaptation capabilities are critical. The approach consists of three main thrusts to enable the desired learning and adaptation: (i) Development of algorithms to efficiently learn optimal control policies and dynamics models through sharing the learning and adaptation between various instantiations of platforms and environments. (ii) Creation of control learning algorithms which can be run on low-cost, low-power mobile platforms. (iii) Development of algorithms for online improvement of policy performance in a minimal number of real-world trials. The proposed research will advance learning and adaptation capabilities of practical cyberphysical systems. The proposed approach will be generally applicable and lead to a new class of learning and adapting systems that are able to leverage shared properties between multiple tasks to significantly speed up learning and adaptation. Success in this research project will bring society closer to solving the grand challenge of teams of mobile, disposable, search and rescue robots which can robustly locomote through uncertain and novel environments, finding survivors in disaster situations, while removing risk from rescuers. This project will provide interdisciplinary training through research and classwork for undergraduate and graduate students in creating systems which intimately couple the cyber and physical aspects in robotic and living mobile platforms. Through the SUPERB summer program, under-represented students in engineering will experience research in learning and robotics.